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Abstract #0445

Calibrationless Parallel Imaging Reconstruction Using Hankel Tensor Completion (HTC)

Yilong Liu1,2, Jun Cao1,2, Mengye Lyu1,2, and Ed X. Wu1,2

1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, People's Republic of China, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, People's Republic of China

Autocalibrating parallel imaging requires sufficient autocalibration signals (ACS) for reliable estimation of coil sensitivity. However, this is not feasible in some applications, for example, spectroscopic imaging where matrix size is relatively small. Recent publications (SAKE, P-LORAKS, and ALOHA, etc.) proposed to construct k-space data into block-wise Hankel matrix, and perform parallel imaging reconstruction with low rank matrix completion. In this study, we proposed to construct a block-wise Hankel tensor, and use tensor completion techniques to synthesize the unacquired samples. This method can also be extended to reconstruct multiple slices simultaneously and provide more accurate reconstruction.

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